The increasing adoption of solar photovoltaic (PV) systems as a renewable energy source is driven by their ability to provide clean, sustainable power. However, dust accumulation on solar panels significantly impacts their efficiency by reducing the amount of sunlight reaching the photovoltaic cells, leading to a decrease in energy output. This project aims to develop an automated cleaning system to address the efficiency losses caused by soiling on solar PV panels. The system employs a rotating brush mechanism driven by a DC motor and controlled by an Arduino microcontroller, which automates the cleaning process while minimizing water usage and manual intervention. The experimental results demonstrate that the automated cleaning system can restore solar panel efficiency by up to 18% under optimal conditions, thereby enhancing power output and reducing the operational costs associated with manual cleaning. This improvement not only increases energy yield but also extends the operational life of the solar PV systems by preventing potential damage caused by dirt buildup. The system’s cost-effectiveness, scalability, and reduced reliance on manual labor make it particularly suitable for large-scale solar installations where regular cleaning is both labor-intensive and hazardous. Moreover, this work highlights the importance of optimizing water usage in the cleaning process, making the system more sustainable, especially in arid regions. By focusing on a dry-brush mechanism, the design minimizes water consumption while maintaining effective cleaning performance. This study's findings underscore the importance of regular, efficient, and cost-effective cleaning methods to maintain solar PV system performance.